AI-Driven Energy Centered Maintenance

This third edition provides a comprehensive update and expansion on the principles and practices of energy-centered maintenance (ECM). It combines advanced concepts with actionable strategies to enhance equipment energy efficiency, reliability, and availability. By integrating cutting-edge developments in artificial intelligence, machine learning, and predictive maintenance, the book offers a modernized approach to facility management that aligns with digital transformation trends. Designed as a self-study guide and reference for energy engineers, facility managers, and maintenance professionals, this edition provides invaluable knowledge on data-driven and AI-driven maintenance strategies, energy performance optimization, and the integration of smart technologies into maintenance planning. Through practical insights, case studies, and real-world applications, it emphasizes sustainability, operational excellence, and cost-efficiency. Tailored for engineers, facility managers, students, and decision-makers, this edition equips readers with the tools and knowledge needed to implement ECM effectively in modern facilities. It bridges theoretical foundations with real-world applications, demonstrating ECM's critical role in reducing energy consumption, enhancing equipment performance, and supporting sustainable, AI-driven facility management practices.